A Modeling Study on the Effect of Interstate Mobility Restrictions on the SARS-CoV-2 Pandemic.

Mobility is a crucial element in comprehending the possible expansion of the transmission chain in an epidemic. In the initial phases, strategies for containing cases can be directly linked to population mobility restrictions, especially when only non-pharmaceutical measures are available. During the pandemic of COVID-19 in Brazil, mobility limitation measures were strongly opposed by a large portion of the population. Hypothetically, if the population had supported such measures, the sharp rise in the number of cases could have been suppressed. In this context, computational modeling offers systematic methods for analyzing scenarios about the development of the epidemiological situation taking into account specific conditions. In this study, we examine the impacts of interstate mobility in Brazil. To do so, we develop a metapopulational model that considers both intra and intercompartmental dynamics, utilizing graph theory. We use a parameter estimation technique that allows us to infer the effective reproduction number in each state and estimate the time-varying transmission rate. This makes it possible to investigate scenarios related to mobility and quantify the effect of people moving between states and how certain measures to limit movement might reduce the impact of the pandemic. Our results demonstrate a clear association between the number of cases and mobility, which is heightened when states are closer to each other. This serves as a proof of concept and shows how reducing mobility in more heavily trafficked areas can be more effective.

An Overview of the World Current and Future Assessment of Novel COVID-19 Trajectory, Impact, and Potential Preventive Strategies at Healthcare Settings.

This study is an overview of the current and future trajectory, as well as the impact of the novel Coronavirus (COVID-19) in the world and selected countries including the state of Kuwait. The selected countries were divided into two groups: Group A (China, Switzerland, and Ireland) and Group B (USA, Brazil, and India) based on their outbreak containment of this virus. Then, the actual data for each country were fitted to a regression model utilizing the excel solver software to assess the current and future trajectory of novel COVID-19 and its impact. In addition, the data were fitted using the Susceptible-Infected-Recovered (SIR) Model. The Group A trajectory showed an "S" shape trend that suited a logistic function with r2 > 0.97, which is an indication of the outbreak control. The SIR models for the countries in this group showed that they passed the expected 99% end of pandemic dates. Group B, however, exhibited a continuous increase of the total COVID-19 new cases, that best suited an exponential growth model with r2 > 0.97, which meant that the outbreak is still uncontrolled. The SIR models for the countries in this group showed that they are still relatively far away from reaching the expected 97% end of pandemic dates. The maximum death percentage varied from 3.3% (India) to 7.2% with USA recording the highest death percentage, which is virtually equal to the maximum death percentage of the world (7.3%). The power of the exponential model determines the severity of the country's trajectory that ranged from 11 to 19 with the USA and Brazil having the highest values. The maximum impact of this COVID-19 pandemic occurred during the uncontrolled stage (2), which mainly depended on the deceptive stage (1). Further, some novel potential containment strategies are discussed. Results from both models showed that the Group A countries contained the outbreak, whereas the Group B countries still have not reached this stage yet. Early measures and containment strategies are imperative in suppressing the spread of COVID-19.

A collaborative initiative for the containment of antimicrobial resistance in Mexico.

Antimicrobial resistance exacts worldwide an increasingly significant clinical and economic toll. Despite the international calls for urgent action, antimicrobial use and resistance have been low on the Mexican government's policy agenda. In early 2010, a multidisciplinary group of experts launched a national initiative for containment of antimicrobial resistance that was endorsed by major medical, veterinary and public health institutions. The initiative called for seven priority actions including the creation of an ad hoc intersectoral advisory group, a requirement that human and veterinary antibiotics be dispensed only with prescription, and the establishment of effective surveillance systems. A consensus document was disseminated among key decision-makers at the ministries of Health and Agriculture and the legislature. The Ministry of Health (MoH) enacted a decree effective as of August 2010, which enforced the regulations that required medical prescriptions for the sale of human antibiotics. While the information disseminated by the MoH did focus on the dangers of self-medication, it failed to highlight the inherent perils of antibiotic resistance or the consequences of antibiotic use in food-animals. Following the decree, there was a surge of medical offices controlled by retail pharmacies. In the veterinary sector, voluntary guidelines were developed for good husbandry practices, including antibiotic use in food animals; five antimicrobials for use in food-animals were banned. No intersectoral advisory group or surveillance systems were established. This study describes a bottom-top approach in Mexico for the development of a national strategy to improve antibiotic use and contain antimicrobial resistance. Its experiences suggest that, in countries such as Mexico that lack strong regulatory systems and surveillance capacities, a more systemic approach is warranted. Future efforts should begin with early involvement of key stakeholders and informing policy makers, professionals and the population at large about the critical importance of antibiotic resistance.